The kind of problems we solve.

The challenge. A multi-channel seller can read revenue easily enough — but how do you know the real, per-order profit once fees, ads, returns, and landed cost are accounted for, across every channel, today?

Our approach. Ingest each channel, payment and logistics API into one normalized data model. Compute per-SKU P&L server-side, reconcile it against settlements and bank statements, and surface it in a control panel the operations team lives in.

The outcome. One reconciled view of profitability, updated continuously — so pricing, purchasing and ad spend decisions rest on a number the team trusts.

The challenge. A finance team is reconciling dozens of bank, card and payment-processor statements by hand every month — slow, error-prone, and impossible to audit with confidence.

Our approach. Build parsers for every statement format, post each line into an append-only ledger, match transactions automatically, and flag only the exceptions for a human — with a full audit trail behind every number.

The outcome. Month-end that takes an afternoon instead of a fortnight, and a ledger that stands up to scrutiny line by line.

The challenge. Stock is scattered across warehouses, 3PLs and in-transit shipments. Planning happens in spreadsheets, and stockouts and overstock both quietly eat margin.

Our approach. Unify warehouse, supplier and sales-velocity data into one inventory model, add batch and expiry logic, and build a replenishment engine that proposes what to buy, how much, and when.

The outcome. A single live picture of inventory across the whole network, and reorder decisions driven by data instead of gut feel.